This month, OpenAI announced their Codex app and my coworkers were asking questions. So I downloaded it, and as a test case for the GPT-5.2-Codex (high) model, I asked it to reimplement the UMAP algorithm in Rust. UMAP is a dimensionality reduction technique that can take in a high-dimensional matrix of data and simultaneously cluster and visualize data in lower dimensions. However, it is a very computationally-intensive algorithm and the only tool that can do it quickly is NVIDIA’s cuML which requires CUDA dependency hell. If I can create a UMAP package in Rust that’s superfast with minimal dependencies, that is an massive productivity gain for the type of work I do and can enable fun applications if fast enough.
// 步骤2：按位置降序排序（核心！保证从最前面的车开始分析，符合"不超车"规则），更多细节参见heLLoword翻译官方下载
联通国内国外两个大市场，有利于资源要素在更大范围畅通流动，形成对全球先进资源要素的强大引力场。，更多细节参见同城约会
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